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| # Copyright 2023 The TensorFlow Authors. All Rights Reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| """Tests for factory functions.""" | |
| # Import libraries | |
| from absl.testing import parameterized | |
| import tensorflow as tf, tf_keras | |
| from tensorflow.python.distribute import combinations | |
| from official.vision.configs import backbones as backbones_cfg | |
| from official.vision.configs import backbones_3d as backbones_3d_cfg | |
| from official.vision.configs import common as common_cfg | |
| from official.vision.modeling import backbones | |
| from official.vision.modeling.backbones import factory | |
| class FactoryTest(tf.test.TestCase, parameterized.TestCase): | |
| def test_resnet_creation(self, model_id): | |
| """Test creation of ResNet models.""" | |
| network = backbones.ResNet( | |
| model_id=model_id, se_ratio=0.0, norm_momentum=0.99, norm_epsilon=1e-5) | |
| backbone_config = backbones_cfg.Backbone( | |
| type='resnet', | |
| resnet=backbones_cfg.ResNet(model_id=model_id, se_ratio=0.0)) | |
| norm_activation_config = common_cfg.NormActivation( | |
| norm_momentum=0.99, norm_epsilon=1e-5, use_sync_bn=False) | |
| factory_network = factory.build_backbone( | |
| input_specs=tf_keras.layers.InputSpec(shape=[None, None, None, 3]), | |
| backbone_config=backbone_config, | |
| norm_activation_config=norm_activation_config) | |
| network_config = network.get_config() | |
| factory_network_config = factory_network.get_config() | |
| self.assertEqual(network_config, factory_network_config) | |
| def test_efficientnet_creation(self, model_id, se_ratio): | |
| """Test creation of EfficientNet models.""" | |
| network = backbones.EfficientNet( | |
| model_id=model_id, | |
| se_ratio=se_ratio, | |
| norm_momentum=0.99, | |
| norm_epsilon=1e-5) | |
| backbone_config = backbones_cfg.Backbone( | |
| type='efficientnet', | |
| efficientnet=backbones_cfg.EfficientNet( | |
| model_id=model_id, se_ratio=se_ratio)) | |
| norm_activation_config = common_cfg.NormActivation( | |
| norm_momentum=0.99, norm_epsilon=1e-5, use_sync_bn=False) | |
| factory_network = factory.build_backbone( | |
| input_specs=tf_keras.layers.InputSpec(shape=[None, None, None, 3]), | |
| backbone_config=backbone_config, | |
| norm_activation_config=norm_activation_config) | |
| network_config = network.get_config() | |
| factory_network_config = factory_network.get_config() | |
| self.assertEqual(network_config, factory_network_config) | |
| def test_mobilenet_creation(self, model_id, filter_size_scale): | |
| """Test creation of Mobilenet models.""" | |
| network = backbones.MobileNet( | |
| model_id=model_id, | |
| filter_size_scale=filter_size_scale, | |
| norm_momentum=0.99, | |
| norm_epsilon=1e-5) | |
| backbone_config = backbones_cfg.Backbone( | |
| type='mobilenet', | |
| mobilenet=backbones_cfg.MobileNet( | |
| model_id=model_id, filter_size_scale=filter_size_scale)) | |
| norm_activation_config = common_cfg.NormActivation( | |
| norm_momentum=0.99, norm_epsilon=1e-5, use_sync_bn=False) | |
| factory_network = factory.build_backbone( | |
| input_specs=tf_keras.layers.InputSpec(shape=[None, None, None, 3]), | |
| backbone_config=backbone_config, | |
| norm_activation_config=norm_activation_config) | |
| network_config = network.get_config() | |
| factory_network_config = factory_network.get_config() | |
| self.assertEqual(network_config, factory_network_config) | |
| def test_spinenet_creation(self, model_id): | |
| """Test creation of SpineNet models.""" | |
| input_size = 128 | |
| min_level = 3 | |
| max_level = 7 | |
| input_specs = tf_keras.layers.InputSpec( | |
| shape=[None, input_size, input_size, 3]) | |
| network = backbones.SpineNet( | |
| input_specs=input_specs, | |
| min_level=min_level, | |
| max_level=max_level, | |
| norm_momentum=0.99, | |
| norm_epsilon=1e-5) | |
| backbone_config = backbones_cfg.Backbone( | |
| type='spinenet', | |
| spinenet=backbones_cfg.SpineNet(model_id=model_id)) | |
| norm_activation_config = common_cfg.NormActivation( | |
| norm_momentum=0.99, norm_epsilon=1e-5, use_sync_bn=False) | |
| factory_network = factory.build_backbone( | |
| input_specs=tf_keras.layers.InputSpec( | |
| shape=[None, input_size, input_size, 3]), | |
| backbone_config=backbone_config, | |
| norm_activation_config=norm_activation_config) | |
| network_config = network.get_config() | |
| factory_network_config = factory_network.get_config() | |
| self.assertEqual(network_config, factory_network_config) | |
| def test_revnet_creation(self, model_id): | |
| """Test creation of RevNet models.""" | |
| network = backbones.RevNet( | |
| model_id=model_id, norm_momentum=0.99, norm_epsilon=1e-5) | |
| backbone_config = backbones_cfg.Backbone( | |
| type='revnet', | |
| revnet=backbones_cfg.RevNet(model_id=model_id)) | |
| norm_activation_config = common_cfg.NormActivation( | |
| norm_momentum=0.99, norm_epsilon=1e-5, use_sync_bn=False) | |
| factory_network = factory.build_backbone( | |
| input_specs=tf_keras.layers.InputSpec(shape=[None, None, None, 3]), | |
| backbone_config=backbone_config, | |
| norm_activation_config=norm_activation_config) | |
| network_config = network.get_config() | |
| factory_network_config = factory_network.get_config() | |
| self.assertEqual(network_config, factory_network_config) | |
| def test_resnet_3d_creation(self, model_type): | |
| """Test creation of ResNet 3D models.""" | |
| backbone_cfg = backbones_3d_cfg.Backbone3D(type=model_type).get() | |
| temporal_strides = [] | |
| temporal_kernel_sizes = [] | |
| for block_spec in backbone_cfg.block_specs: | |
| temporal_strides.append(block_spec.temporal_strides) | |
| temporal_kernel_sizes.append(block_spec.temporal_kernel_sizes) | |
| _ = backbones.ResNet3D( | |
| model_id=backbone_cfg.model_id, | |
| temporal_strides=temporal_strides, | |
| temporal_kernel_sizes=temporal_kernel_sizes, | |
| norm_momentum=0.99, | |
| norm_epsilon=1e-5) | |
| def test_mobiledet_creation(self, model_id, filter_size_scale): | |
| """Test creation of Mobiledet models.""" | |
| network = backbones.MobileDet( | |
| model_id=model_id, | |
| filter_size_scale=filter_size_scale, | |
| norm_momentum=0.99, | |
| norm_epsilon=1e-5) | |
| backbone_config = backbones_cfg.Backbone( | |
| type='mobiledet', | |
| mobiledet=backbones_cfg.MobileDet( | |
| model_id=model_id, filter_size_scale=filter_size_scale)) | |
| norm_activation_config = common_cfg.NormActivation( | |
| norm_momentum=0.99, norm_epsilon=1e-5, use_sync_bn=False) | |
| factory_network = factory.build_backbone( | |
| input_specs=tf_keras.layers.InputSpec(shape=[None, None, None, 3]), | |
| backbone_config=backbone_config, | |
| norm_activation_config=norm_activation_config) | |
| network_config = network.get_config() | |
| factory_network_config = factory_network.get_config() | |
| self.assertEqual(network_config, factory_network_config) | |
| if __name__ == '__main__': | |
| tf.test.main() | |